Conversion odelling is the process of measuring marketing performance using machine learning when a subset of conversions cannot be directly connected to ad interactions.

• Conversion modeling refers to observed conversions and uses cookies to connect between ad interactions and conversions.
• Conversion modeling refers to the import of observable conversions into Google Ads that model only the best quality conversions.
• Conversion modeling refers to measuring marketing using machine learning when a subset of conversions can’t connect to ad interactions.
• Conversion modeling refers to the process of creating custom columns in Google Ads to model your conversion data and performance.

The correct answer is: Conversion modeling refers to measuring marketing using machine learning when a subset of conversions can’t connect to ad interactions

Explanation: Conversion modeling is a crucial technique that leverages machine learning to bridge the gaps in your conversion data. In today’s privacy-focused landscape, it’s not always possible to directly link every ad interaction to a conversion due to factors like cookie restrictions, user consent choices (e.g., via Consent Mode), and cross-device journeys. When a subset of conversions cannot be directly observed, conversion modeling uses patterns from observed conversions and other signals to predict the unobserved ones. This creates a more complete and accurate picture of overall campaign performance, enabling better optimization and bidding decisions.

Reference Link: How conversion modeling works – Google Ads Help: https://support.google.com/google-ads/answer/12443859

This official Google Ads Help page provides a comprehensive explanation of conversion modeling, explicitly stating: “Conversion modeling is the use of machine learning to assess the impact of marketing efforts when a subset of conversions can’t be directly linked to ad interactions.”